The Role of Hypernetworks as a Multilevel Methodology for Modelling and Understanding Dynamics of Team Sports Performance
The Role of Hypernetworks as a Multilevel Methodology for Modelling and Understanding Dynamics of Team Sports Performance
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DOI：
10.1007/s40279-019-01104-x
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发表时间：
2019-09-01
期刊：
影响因子：
9.8
通讯作者：
Garganta, Julio
中科院分区：
文献类型：
--
作者：
Ribeiro, Joao;Davids, Keith;Garganta, Julio
尽管传统科学方法在许多学术领域都很重要，但它很难处理许多复杂适应系统中的相互作用的分析，包括团队运动。这类系统的固有特征(例如突发行为)需要更全面的方法来衡量和分析，以了解系统的特性。复杂性科学包括一种研究集体适应系统的整体方法，它整合了其他理论和方法(如生态动力学和社会网络分析)的概念和工具，以解释这类系统在其自然环境中的功能。多层次网络和超网络构成了新的和强大的方法工具，用于在更复杂的分析水平上评估团队动态，增加它们对团队运动中竞技表现的影响的潜力。在这里，我们讨论了从多级网络和超网络的研究中衍生出来的概念和工具如何有可能揭示运动队作为复杂的、适应性的社会系统的关键属性。这种类型的分析可以提供关于团队表现的有价值的信息，教练、运动科学家和表现分析师可以利用这些信息来加强练习和训练。我们考察了网络科学作为复杂性科学的一个分支学科在研究运动队在练习和比赛过程中关系结构的动态变化的相关性。具体地说，我们探讨了实施多级网络的好处，与传统网络技术形成了对比，强调了未来研究的可能性。最后，我们推荐了增强超网络在多个层次上分析团队动态的适用性的方法。
Despite its importance in many academic fields, traditional scientific methodologies struggle to cope with analysis of interactions in many complex adaptive systems, including team sports. Inherent features of such systems (e.g. emergent behaviours) require a more holistic approach to measurement and analysis for understanding system properties. Complexity sciences encompass a holistic approach to research on collective adaptive systems, which integrates concepts and tools from other theories and methods (e.g. ecological dynamics and social network analysis) to explain functioning of such systems in their natural environments. Multilevel networks and hypernetworks comprise novel and potent methodological tools for assessing team dynamics at more sophisticated levels of analysis, increasing their potential to impact on competitive performance in team sports. Here, we discuss how concepts and tools derived from studies of multilevel networks and hypernetworks have the potential for revealing key properties of sports teams as complex, adaptive social systems. This type of analysis can provide valuable information on team performance, which can be used by coaches, sport scientists and performance analysts for enhancing practice and training. We examine the relevance of network sciences, as a sub-discipline of complexity sciences, for studying the dynamics of relational structures of sports teams during practice and competition. Specifically, we explore the benefits of implementing multilevel networks, in contrast to traditional network techniques, highlighting future research possibilities. We conclude by recommending methods for enhancing the applicability of hypernetworks in analysing team dynamics at multiple levels.